0aa422b7911f33dcc5297abed6449be7cc01a517,mr/preprocessing.py,,bandpass,#Any#Any#Any#Any#,30

Before Change

    gaussian = ifftn(fourier_gaussian(fftn(image), lshort))
    result = gaussian - boxcar
    result -= threshold  // Features must be this level above the background.
    return result.real.clip(min=0.)


def scale_to_gamut(image, original_dtype):
    max_value = np.iinfo(original_dtype).max

After Change

    boxcar = uniform_filter(image, 2*llong+1, **settings)
    gaussian = ifftn(fourier_gaussian(fftn(image), lshort))
    result = gaussian - boxcar
    return np.where(result > threshold, result.real, 0)


def scale_to_gamut(image, original_dtype):
    max_value = np.iinfo(original_dtype).max

Instances